Understanding the Rural Tilt among Financial Co-operatives in Canada
Bibliographic record
Abstract
ABSTRACTThis mixed methods study examines whether the rural/urban distribution of credit union/caisse populaire branches differs significantly from the general urban/rural demographic pattern in Canada. It also explores whether their distribution is different from that of banks, looking at the cases of Québec and Atlantic Canada. The study finds a rural tilt among financial cooperatives in Canada, and seven key informants present their views on the results. Their responses are categorized in two main themes: why financial cooperatives are overrepresented in rural and small town areas, and why they are under-represented in urban ones. A discussion follows, and directions for further study are provided.RÉSUMÉCette étude utilisant des méthodes combinées examine si la distribution des succursales de coopératives d’épargne et de crédit / caisses populaires en milieu rural et urbain diffère de façon importante de la tendance démographique générale des milieux urbains et ruraux au Canada. Elle aborde aussi la question de savoir si leur distribution est différente de celle des banques en observant le cas du Québec et du Canada atlantique. L’étude révèle une tendance rurale chez les coopératives financières du Canada, et sept répondants clés donnent leur opinion sur les résultats. Les réponses des intervenants sont divisées en deux thèmes principaux : pourquoi les coopératives sont surreprésentées dans les milieux ruraux et les petites villes et pourquoi elles sont sous-représentées dans les milieux urbains. Un débat s’ensuit, et des lignes directrices sont fournies aux fins d’une étude plus approfondie.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".